CN117555029A - Single well quantitative division method for geomechanical layer of oil and gas reservoir - Google Patents
Single well quantitative division method for geomechanical layer of oil and gas reservoir Download PDFInfo
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Abstract
The invention provides a single well quantitative division method of a geomechanical layer of an oil and gas reservoir, which is applicable to the field of petroleum and natural gas geology and coal gas geology. Collecting a drilling rock core, and carrying out triaxial rock mechanical experiments and differential strain ground stress tests to obtain test parameters; determining the dominant azimuth of the present ground stress near the periphery of the well; calculating the elastic modulus, the compressive strength, the triaxial present ground stress, the reservoir pressure and the stress concentration coefficient, and constructing the relation between experimental test data and logging calculation data to correct the result; the entropy weight method is utilized to respectively obtain the parameters weight values of the horizontal minimum principal stress, the horizontal principal stress difference, the elastic modulus, the included angle between the dominant azimuth of the current ground stress and the trend of the natural fracture, the density of the natural fracture and the stress concentration coefficient, and the geomechanical layer of the single well oil and gas reservoir is quantitatively divided by constructing the geomechanical layer index Q. The method has the advantages of comprehensive and strict consideration factors, strong operability and high reliability of geomechanical layer division results.
Description
Technical Field
The invention relates to a single well quantitative division method for geomechanical layers of oil and gas reservoirs, which is particularly suitable for the field of petroleum and natural gas geology and coal gas geology.
Background
The ground stress, the natural cracks and the rock mechanical properties are mutually influenced, the coupling effect among the ground stress, the natural cracks and the rock mechanical properties are comprehensively considered, and the quantitative division of the geomechanical layer is significant for oil and gas exploration and development.
Current research is focused mainly on rock mechanics layer division. The invention patent of application publication number CN112765785A provides a multi-scale rock mechanical layer logging dividing method, wherein a rock mechanical layer discrimination index is constructed by calculating dynamic and static mechanical parameters of rock and adopting an equal frequency conversion method; dividing a single-scale rock mechanical layer and calculating the density of the rock through cluster analysis of the rock mechanical parameters of logging and point casting; and changing a threshold value, and performing cluster analysis on rock mechanical parameters of logging throwing points in a circulating way to finish conventional logging division of rock mechanical layers with different scales. The invention patent of application publication number CN114184764A provides a method and a system for dividing a rock mechanical layer of a compact carbonate reservoir, and static rock mechanical parameters of a plurality of core samples are respectively obtained; respectively acquiring dynamic rock mechanical parameters of depth points corresponding to each core sample; acquiring static rock mechanical parameters corrected by each depth point based on the static rock mechanical parameters of each core sample, the dynamic rock mechanical parameters of the corresponding depth point and the dynamic rock mechanical parameters of each depth point; based on the static rock mechanical parameters corrected by each depth point and the reservoir rock mechanical index calculation model, rock mechanical indexes of each depth point are calculated respectively; based on the single well crack development characteristics and the rock mechanical index of each depth point, the method can divide the rock mechanical layer of the reservoir. The invention patent of application publication number CN116595724A provides a rock mechanical layer dividing method, a system, electronic equipment and a medium, and performs triaxial stress test on rock samples with different mechanical properties by setting different confining pressures to obtain a stress-strain curve, young modulus and crack development mode; classifying the crack modes of the rock sample according to the differences of the rock breaking characteristics, providing a mechanical layer division index based on the differences of the crack modes, determining the mechanical layer division index limit corresponding to different crack modes, dividing the mechanical layer interface, establishing a coupling factor of energy release and crack formation after the rock sample is broken according to the characteristics of a stress-strain curve, and evaluating the development strength of the rock crack in the mechanical layer.
Research into reservoir geomechanics has focused on numerical simulation construction. The invention patent with the application publication number of CN116299672A provides a fracture-cavity type reservoir geomechanical heterogeneity-anisotropy modeling method, and the three-dimensional fracture-cavity body fine carving and geogeometric modeling are realized through three-dimensional seismic interpretation and fracture-cavity type reservoir seismic multi-attribute inversion; and (3) performing induced division on the geomechanical grids of the fracture-cavity type reservoir, and performing geomechanical anisotropic modeling on the fracture-cavity type reservoir according to the fine carving and geogeometric modeling of the three-dimensional fracture-cavity body and the distribution of the three-dimensional rock mechanical parameters. The patent of the invention of the authority publication number CN105549082B provides a method and a system for establishing a three-dimensional geomechanical field of an ultra-deep carbonate reservoir, and an earthquake superposition velocity field containing three-dimensional coordinate information is established according to basic data of an earthquake work area; calculating the layer velocity along the layer according to the seismic superposition velocity field and the seismic interpretation horizon data, and determining the corresponding seismic average velocity according to the layer velocity to obtain a seismic average velocity field; according to the coordinate range of the network of the earthquake work area, carrying out three-dimensional data interpolation on the earthquake average velocity field through earthquake interpretation horizon control to obtain an earthquake three-dimensional velocity field; and determining lithology physical parameters according to the three-dimensional seismic velocity field, further calculating the stratum pressure and the geological stress of the seismic work area, and constructing a three-dimensional geomechanical field.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides the single well quantitative division method for the geomechanical layer of the oil and gas reservoir, which has comprehensive consideration factors, strong operability and high result reliability, comprehensively optimizes the horizontal minimum principal stress, the horizontal principal stress difference, the current dominant azimuth of the ground stress and the included angle of the natural fracture trend, the elastic modulus, the natural fracture density and the stress concentration coefficient, and constructs the index Q of the geomechanical layer of the reservoir.
In order to achieve the above object, the invention provides a single well quantitative division method for geomechanical layers of oil and gas reservoirs, which is characterized in that: collecting cores of different depths of drilling, processing the drilling cores, and carrying out triaxial rock mechanical experiments and differential strain ground stress tests on the drilling cores to obtain mechanical data of different drilling cores; collecting imaging logging data, calculating natural crack densities of different depth sections, and determining the dominant azimuth of the present ground stress near different depths Duan Jingzhou; collecting conventional logging data of the well drilling, calculating and obtaining elastic modulus, compressive strength, present ground stress, reservoir pressure and stress concentration coefficient, and correcting results by constructing the relation between experimental test data and logging calculation data; and respectively obtaining the parameters of the horizontal minimum principal stress, the horizontal principal stress difference, the elastic modulus, the included angle between the dominant azimuth of the current ground stress and the trend of the natural cracks, the density of the natural cracks and the stress concentration coefficient by using an entropy weight method, constructing a geomechanical layer index Q, and quantitatively dividing the geomechanical layer of the single-well oil-gas reservoir according to the parameters.
The method comprises the following specific steps:
step 1, collecting a plurality of full-diameter rock cores with different depth measuring points in target drilling, recording the collecting depth in each full-diameter rock core, processing each full-diameter rock core into a sector with the radius of 5cm and the height of 5cm and a plunger with the diameter of 2.5cm and the height of 5cm, and grinding the upper end face and the lower end face of the sector and the plunger to be parallel, wherein the central angle of the sector is 90 degrees, and attaching a strain gauge on two rectangular faces and an arc face of the sector;
step 2, carrying out triaxial rock mechanics experiments and differential strain ground stress tests on all the plungers and the segments respectively, so as to obtain actual measurement data of the plungers and the segments: modulus of elasticity, compressive strength, horizontal maximum principal stress, horizontal minimum principal stress, and vertical principal stress;
step 3, collecting data of the target well drilling, including conventional well logging, heart tonifying elevation and heart tonifying height, and acquiring elastic modulus, compressive strength, current ground stress and reservoir pressure well logging calculation results of different depths of the target well drilling by using an empirical formula;
step 4, because the actual measurement information of the measurement points of different depths of the well obtained through actual measurement in step 2 is discrete but high in accuracy, and the calculation result obtained by using the logging information in step 3 is continuous and has errors, the actual measurement data and the logging calculation result are correspondingly arranged, a quantized relation between the actual measurement data and corresponding parameters contained in the logging calculation result is established, the logging calculation result of the elastic modulus, the compressive strength, the current ground stress and the reservoir pressure of the well depth obtained by an empirical formula in step 3 is corrected by using the actual measurement data, and the horizontal main stress difference of the well at different depths of the well is calculated;
step 5, collecting imaging logging information of the target well drilling, picking up natural crack occurrence, well wall collapse and well drilling induced joint information, calculating natural crack density of the target well drilling, dividing the target well drilling into n sections, determining the dominant azimuth of the present ground stress near the periphery of the target well drilling according to the relation between the well wall collapse, the well drilling induced joint and the present ground stress direction, and obtaining the included angle between the dominant azimuth of the present ground stress of each of the n well logging depth sections and the natural crack trend through an interpolation method;
step 6, obtaining logging calculation results of the corrected elastic modulus, compressive strength, current ground stress and reservoir pressure by utilizing the step 4, and calculating stress concentration coefficients of different depth sections of the target drilling divided into n sections;
step 7, selecting the horizontal minimum principal stress, the horizontal principal stress difference, the current dominant azimuth of the ground stress and the trend included angle of the natural cracks, the elastic modulus, the natural crack density and the stress concentration coefficient of the different depth sections obtained in the steps 2-6, carrying out normalization treatment on each parameter, and limiting the numerical value in the range of 0-1; wherein: the elastic modulus and the natural fracture density are positive parameters, the horizontal minimum main stress, the horizontal main stress difference, the current ground stress dominant orientation, the natural fracture trend included angle and the stress concentration coefficient are negative parameters, the entropy weight method is further utilized to obtain each parameter weight value, finally, each normalized parameter is utilized to construct a geomechanical layer index Q, and the geomechanical layer of the single-well oil-gas reservoir is quantitatively divided according to the geomechanical layer index Q.
Further, the empirical formula adopted for acquiring the well logging calculation results of different depths of the target well drilling in the step 3 is as follows:
the elastic modulus logging empirical calculation formula:
wherein: mu is the Poisson's ratio, G is the shear modulus, E is the rock elastic modulus, ρ b Represents the formation bulk density, Δt s For formation transverse wave time difference, deltat p Is the formation longitudinal wave time difference;
compressive strength logging empirical calculation formula:
σ c ＝a·E·(1-V sh )+b·E·V sh (4)
wherein: sigma (sigma) c Is compressive strength, E is elastic modulus of rock, V sh For the clay content, a and b are coefficients;
the well logging calculation of the ground stress adopts a combined spring model, and the empirical calculation formula is as follows:
wherein: s is S H Is the horizontal maximum principal stress, S h Is the horizontal minimum principal stress, S v Alpha is Biot coefficient, E is Young's modulus of rock, mu is Poisson's ratio of rock, P o Epsilon for reservoir pressure H And epsilon h Horizontal maximum and minimum principal strains, respectively;
logging calculation of reservoir pressure adopts an Eton method, and an empirical calculation formula is as follows:
wherein: p (P) o Is reservoir pressure; s and P n Respectively representing overburden pressure and hydrostatic column pressure; c represents the Eton coefficient; Δt (delta t) n And deltat are the acoustic time difference on the normal compaction trend line and the actual acoustic time difference of the formation, respectively.
In step 4, a BP neural network method or a convolutional neural network method is used for establishing a quantitative relation between measured data and a logging calculation result.
Further, in step 5, the relationship between the borehole wall breakout, the induced joint of drilling and the current ground stress direction is: the direction of the well drilling induced joint is vertical to the direction of the horizontal minimum principal stress, and the long axis direction of the well wall breakout is parallel to the direction of the horizontal minimum principal stress; and calculating the included angle between the current ground stress dominant azimuth and the natural fracture trend of the logging depth section by adopting the Kriging method.
Further, in the step 6, the calculation formula of the stress concentration coefficient ω is:
wherein: s is S H For the horizontal maximum principal stress, P o For reservoir pressure, sigma c Is compressive strength.
Further, a geomechanical layer index Q is constructed, and the geomechanical layer index Q is utilized to divide geomechanical layers of the single-well oil-gas reservoir, wherein the Q value is I layer when the Q value is within the range of (0.75-1), II layer when the Q value is within the range of (0.50-0.75), III layer when the Q value is within the range of (0.25-0.50), and IV layer when the Q value is within the range of (0-0.25);
the method for constructing the geomechanical layer index Q in the step 7 is as follows:
Q＝m 1 S h * +m 2 ΔS * +m 3 E * +m 4 F d * +m 5 β * +m 6 ω * (9)
wherein: q represents a geomechanical layer index, S h * For normalized horizontal minimum principal stress, Δs represents normalized horizontal principal stress difference, E represents normalized rock elastic modulus, F d * For normalized fracture density, β is the normalized angle between the dominant orientation of the present ground stress and the natural fracture strike, ω is the normalized stress concentration coefficient, m 1 ～m 6 Is a weight coefficient.
The beneficial effects are that:
the lithology of the sedimentary rock formations of the hydrocarbon-bearing basin is changeable in the longitudinal direction under the influence of the construction and the sedimentary evolution. The early-stage research is mainly conducted on rock mechanical layers, but the present ground stress, natural cracks and rock mechanical properties are mutually influenced, the coupling effect among the three is comprehensively considered, and quantitative division of the geomechanical layers is conducted, so that the method has important practical guiding significance for the numerical simulation of the present ground stress field and evaluation of engineering desserts, and is beneficial to oil and gas exploration and development.
Drawings
FIG. 1 is a schematic flow chart of a single well quantitative partitioning method for a geomechanical layer of an oil and gas reservoir.
FIG. 2 is a block diagram of a sector and plunger sample for use in the test of the present invention.
Detailed Description
Embodiments of the invention are further described below with reference to the accompanying drawings:
the invention discloses a single well quantitative dividing method of a geomechanical layer of an oil and gas reservoir, which comprises the steps of collecting rock cores of different depths of drilling, processing the drilling rock cores, preparing samples according to requirements, carrying out triaxial rock mechanical experiments and differential strain ground stress tests, and obtaining the elastic modulus, poisson ratio, compressive strength, horizontal maximum main stress, horizontal minimum main stress and vertical main stress of experimental samples; collecting imaging logging data, picking up natural fracture occurrence, well wall collapse and drilling induced joints, calculating natural fracture density, and determining the dominant azimuth of the present ground stress near the periphery of the well according to the relation between the well wall collapse, the drilling induced joints and the present ground stress direction; collecting conventional logging data, calculating and obtaining parameters such as elastic modulus, compressive strength, triaxial present ground stress, reservoir pressure and stress concentration coefficient, and correcting results by constructing the relation between experimental test data and logging calculation data; and respectively obtaining the parameters of the horizontal minimum principal stress, the horizontal principal stress difference, the elastic modulus, the included angle between the dominant azimuth of the present ground stress and the trend of the natural cracks, the density of the natural cracks and the stress concentration coefficient by using an entropy weight method, constructing a geomechanical layer index Q, and quantitatively dividing the geomechanical layer of the single-well oil-gas reservoir according to the parameters.
The specific steps shown in fig. 1 are as follows:
step 1, collecting a plurality of full-diameter cores with different depth measuring points in target drilling, recording the collection depth in each full-diameter core, processing each full-diameter core into a sector with the radius of 5cm and the height of 5cm and a plunger with the diameter of 2.5cm and the height of 5cm, and grinding the upper end face and the lower end face of the sector and the plunger to be parallel as shown in figure 2, wherein the central angle of the sector is 90 degrees, and attaching a strain gauge on two rectangular surfaces and an arc surface of the sector;
step 2, carrying out triaxial rock mechanics experiments and differential strain ground stress tests on all the plungers and the segments respectively, so as to obtain actual measurement data of the plungers and the segments: modulus of elasticity, compressive strength, horizontal maximum principal stress, horizontal minimum principal stress, and vertical principal stress;
step 3, collecting data of the target well drilling, including conventional well logging, heart tonifying elevation and heart tonifying height, and acquiring elastic modulus, compressive strength, current ground stress and reservoir pressure well logging calculation results of different depths of the target well drilling by using an empirical formula;
the empirical formula adopted for obtaining the well logging calculation results of different depths of the target well drilling is as follows:
the elastic modulus logging empirical calculation formula:
wherein: mu is the Poisson's ratio, G is the shear modulus, E is the rock elastic modulus, ρ b Represents the formation bulk density, Δt s For formation transverse wave time difference, deltat p Is the formation longitudinal wave time difference;
compressive strength logging empirical calculation formula:
σ c ＝a·E·(1-V sh )+b·E·V sh (4)
wherein: sigma (sigma) c Is compressive strength, E is elastic modulus of rock, V sh For the clay content, a and b are coefficients;
the well logging calculation of the ground stress adopts a combined spring model, and the empirical calculation formula is as follows:
wherein: s is S H Is the horizontal maximum principal stress, S h Is the horizontal minimum principal stress, S v Alpha is Biot coefficient, E is Young's modulus of rock, mu is Poisson's ratio of rock, P o Epsilon for reservoir pressure H And epsilon h Horizontal maximum and minimum principal strains, respectively;
logging calculation of reservoir pressure adopts an Eton method, and an empirical calculation formula is as follows:
wherein: p (P) o Is reservoir pressure; s and P n Respectively representing overburden pressure and hydrostatic column pressure; c represents the Eton coefficient; Δt (delta t) n And deltat are the acoustic time difference on the normal compaction trend line and the actual acoustic time difference of the formation, respectively.
Step 4, because the actual measurement information of the measurement points of different depths of the well obtained through actual measurement in step 2 is discrete but high in accuracy, and the calculation result obtained by using the logging information in step 3 is continuous and has errors, the actual measurement data and the logging calculation result are correspondingly arranged, a quantized relation between the actual measurement data and corresponding parameters contained in the logging calculation result is established, the logging calculation result of the elastic modulus, the compressive strength, the current ground stress and the reservoir pressure of the well depth obtained by an empirical formula in step 3 is corrected by using the actual measurement data, and the horizontal main stress difference of the well at different depths of the well is calculated; and establishing a quantitative relation between the measured data and the logging calculation result by using a BP neural network method or a convolutional neural network method.
Step 5, collecting imaging logging information of the target well drilling, picking up natural crack occurrence, well wall collapse and well drilling induced joint information, calculating natural crack density of the target well drilling, dividing the target well drilling into n sections, determining the dominant azimuth of the present ground stress near the periphery of the target well drilling according to the relation between the well wall collapse, the well drilling induced joint and the present ground stress direction, and obtaining the included angle between the dominant azimuth of the present ground stress of each of the n well logging depth sections and the natural crack trend through an interpolation method; the relation between the well wall caving, the well drilling induced joint and the current ground stress direction is as follows: the direction of the well drilling induced joint is vertical to the direction of the horizontal minimum principal stress, and the long axis direction of the well wall breakout is parallel to the direction of the horizontal minimum principal stress; and calculating the included angle between the current ground stress dominant azimuth and the natural fracture trend of the logging depth section by adopting the Kriging method.
Step 6, obtaining logging calculation results of the corrected elastic modulus, compressive strength, current ground stress and reservoir pressure by utilizing the step 4, and calculating stress concentration coefficients of different depth sections of the target drilling divided into n sections;
the calculation formula of the stress concentration coefficient omega is as follows:
wherein: s is S H For the horizontal maximum principal stress, P o For reservoir pressure, sigma c Is compressive strength.
Step 7, selecting the horizontal minimum principal stress, the horizontal principal stress difference, the current dominant azimuth of the ground stress and the trend included angle of the natural cracks, the elastic modulus, the natural crack density and the stress concentration coefficient of the different depth sections obtained in the steps 2-6, carrying out normalization treatment on each parameter, and limiting the numerical value in the range of 0-1; wherein: the elastic modulus and the natural fracture density are positive parameters, the horizontal minimum main stress, the horizontal main stress difference, the current ground stress dominant orientation, the natural fracture trend included angle and the stress concentration coefficient are negative parameters, the entropy weight method is further utilized to obtain each parameter weight value, finally, each normalized parameter is utilized to construct a geomechanical layer index Q, and the geomechanical layer of the single-well oil-gas reservoir is quantitatively divided according to the geomechanical layer index Q. The Q value is I layer when the value is within the range of (0.75-1), II layer when the value is within the range of (0.50-0.75), III layer when the value is within the range of (0.25-0.50), and IV layer when the value is within the range of (0-0.25).
The equation for constructing geomechanical layer index Q is as follows:
Q＝m 1 S h * +m 2 ΔS * +m 3 E * +m 4 F d * +m 5 β * +m 6 ω * (9)
wherein: q represents a geomechanical layer index, S h * For normalized horizontal minimum principal stress, Δs represents normalized horizontal principal stress difference, E represents normalized rock elastic modulus, F d * For normalized fracture density, β is the normalized angle between the dominant orientation of the present ground stress and the natural fracture strike, ω is the normalized stress concentration coefficient, m 1 ～m 6 Is a weight coefficient.
Claims (7)
1. A single well quantitative division method for a geomechanical layer of an oil and gas reservoir is characterized by comprising the following steps of: collecting cores of different depths of drilling, processing the drilling cores, and carrying out triaxial rock mechanical experiments and differential strain ground stress tests on the drilling cores to obtain mechanical data of different drilling cores; collecting imaging logging data, calculating natural crack densities of different depth sections, and determining the dominant azimuth of the present ground stress near different depths Duan Jingzhou; collecting conventional logging data of the well drilling, calculating and obtaining elastic modulus, compressive strength, present ground stress, reservoir pressure and stress concentration coefficient, and correcting results by constructing the relation between experimental test data and logging calculation data; and respectively obtaining the parameters of the horizontal minimum principal stress, the horizontal principal stress difference, the elastic modulus, the included angle between the dominant azimuth of the current ground stress and the trend of the natural cracks, the density of the natural cracks and the stress concentration coefficient by using an entropy weight method, constructing a geomechanical layer index Q, and quantitatively dividing the geomechanical layer of the single-well oil-gas reservoir according to the parameters.
2. The method for quantitatively dividing the geomechanical layer of the oil and gas reservoir into single wells according to claim 1 is characterized by comprising the following specific steps:
step 1, collecting a plurality of full-diameter rock cores with different depth measuring points in target drilling, recording the collecting depth in each full-diameter rock core, processing each full-diameter rock core into a sector with the radius of 5cm and the height of 5cm and a plunger with the diameter of 2.5cm and the height of 5cm, and grinding the upper end face and the lower end face of the sector and the plunger to be parallel, wherein the central angle of the sector is 90 degrees, and attaching a strain gauge on two rectangular faces and an arc face of the sector;
step 2, carrying out triaxial rock mechanics experiments and differential strain ground stress tests on all the plungers and the segments respectively, so as to obtain actual measurement data of the plungers and the segments: modulus of elasticity, compressive strength, horizontal maximum principal stress, horizontal minimum principal stress, and vertical principal stress;
step 3, collecting data of the target well drilling, including conventional well logging, heart tonifying elevation and heart tonifying height, and acquiring elastic modulus, compressive strength, current ground stress and reservoir pressure well logging calculation results of different depths of the target well drilling by using an empirical formula;
step 4, because the actual measurement information of the measurement points of different depths of the well obtained through actual measurement in step 2 is discrete but high in accuracy, and the calculation result obtained by using the logging information in step 3 is continuous and has errors, the actual measurement data and the logging calculation result are correspondingly arranged, a quantized relation between the actual measurement data and corresponding parameters contained in the logging calculation result is established, the logging calculation result of the elastic modulus, the compressive strength, the current ground stress and the reservoir pressure of the well depth obtained by an empirical formula in step 3 is corrected by using the actual measurement data, and the horizontal main stress difference of the well at different depths of the well is calculated;
step 5, collecting imaging logging information of the target well drilling, picking up natural crack occurrence, well wall collapse and well drilling induced joint information, calculating natural crack density of the target well drilling, dividing the target well drilling into n sections, determining the dominant azimuth of the present ground stress near the periphery of the target well drilling according to the relation between the well wall collapse, the well drilling induced joint and the present ground stress direction, and obtaining the included angle between the dominant azimuth of the present ground stress of each of the n well logging depth sections and the natural crack trend through an interpolation method;
step 6, obtaining logging calculation results of the corrected elastic modulus, compressive strength, current ground stress and reservoir pressure by utilizing the step 4, and calculating stress concentration coefficients of different depth sections of the target drilling divided into n sections;
step 7, selecting the horizontal minimum principal stress, the horizontal principal stress difference, the current dominant azimuth of the ground stress and the trend included angle of the natural cracks, the elastic modulus, the natural crack density and the stress concentration coefficient of the different depth sections obtained in the steps 2-6, carrying out normalization treatment on each parameter, and limiting the numerical value in the range of 0-1; wherein: the elastic modulus and the natural fracture density are positive parameters, the horizontal minimum main stress, the horizontal main stress difference, the current ground stress dominant orientation, the natural fracture trend included angle and the stress concentration coefficient are negative parameters, the entropy weight method is further utilized to obtain each parameter weight value, finally, each normalized parameter is utilized to construct a geomechanical layer index Q, and the geomechanical layer of the single-well oil-gas reservoir is quantitatively divided according to the geomechanical layer index Q.
3. The method for quantitatively dividing the single well of the geomechanical layer of the oil and gas reservoir according to claim 2 is characterized in that the empirical formula adopted for acquiring the logging calculation results of different depths of the target well in the step 3 is as follows:
the elastic modulus logging empirical calculation formula:
wherein: mu is the Poisson's ratio, G is the shear modulus, E is the rock elastic modulus, ρ b Represents the formation bulk density, Δt s For formation transverse wave time difference, deltat p Is the formation longitudinal wave time difference;
compressive strength logging empirical calculation formula:
σ c ＝a·E·(1-V sh )+b·E·V sh (4)
wherein: sigma (sigma) c Is compressive strength, E is elastic modulus of rock, V sh For the clay content, a and b are coefficients;
the well logging calculation of the ground stress adopts a combined spring model, and the empirical calculation formula is as follows:
wherein: s is S H Is the horizontal maximum principal stress, S h Is the horizontal minimum principal stress, S v Alpha is Biot coefficient, E is Young's modulus of rock, mu is Poisson's ratio of rock, P o Epsilon for reservoir pressure H And epsilon h Horizontal maximum and minimum principal strains, respectively;
logging calculation of reservoir pressure adopts an Eton method, and an empirical calculation formula is as follows:
wherein: p (P) o Is reservoir pressure; s and P n Respectively representing overburden pressure and hydrostatic column pressure; c represents the Eton coefficient; Δt (delta t) n And deltat are the acoustic time difference on the normal compaction trend line and the actual acoustic time difference of the formation, respectively.
4. The method for quantitatively dividing the single well of the geomechanical layer of the oil and gas reservoir according to claim 2 is characterized in that in the step 4, a BP neural network method or a convolutional neural network method is used for establishing a quantitative relation between measured data and a logging calculation result.
5. The method for quantitatively dividing the single well of the geomechanical layer of the oil and gas reservoir according to claim 2 is characterized in that the relation between the well wall collapse, the well drilling induced joint and the current ground stress direction in the step 5 is as follows: the direction of the well drilling induced joint is vertical to the direction of the horizontal minimum principal stress, and the long axis direction of the well wall breakout is parallel to the direction of the horizontal minimum principal stress; and calculating the included angle between the current ground stress dominant azimuth and the natural fracture trend of the logging depth section by adopting the Kriging method.
6. The method for quantitatively dividing the single well of the geomechanical layer of the oil and gas reservoir according to claim 2 is characterized in that the calculation formula of the stress concentration coefficient omega in the step 6 is as follows:
wherein: s is S H For the horizontal maximum principal stress, P o For reservoir pressure, sigma c Is compressive strength.
7. The single well quantitative division method for the oil and gas reservoir geomechanical layer according to claim 2 is characterized by comprising the specific steps of constructing a geomechanical layer index Q, dividing the geomechanical layer of the single well oil and gas reservoir by using the geomechanical layer index Q, wherein the Q value is I when the Q value is in the range of (0.75-1), II when the Q value is in the range of (0.50-0.75), III when the Q value is in the range of (0.25-0.50), and IV when the Q value is in the range of (0-0.25);
the method for constructing the geomechanical layer index Q in the step 7 is as follows:
Q＝m 1 S h * +m 2 ΔS * +m 3 E * +m 4 F d * +m 5 β * +m 6 ω * (9)
wherein: q represents a geomechanical layer index, S h * For normalized horizontal minimum principal stress, Δs represents normalized horizontal principal stress difference, E represents normalized rock elastic modulus, F d * Normalized crack density, β is normalized present day ground stressThe included angle between the dominant azimuth and the natural fracture trend is the normalized stress concentration coefficient, m 1 ～m 6 Is a weight coefficient.
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